Senior Robotics RL Engineer

Technology Innovation Institute (TII) is a publicly funded research institute based in Abu Dhabi, United Arab Emirates. It boasts a diverse community of leading scientists, engineers, mathematicians, and researchers dedicated to transforming challenges into pioneering research and technology prototypes to advance society. This role is part of TII’s Robotics Research Center.

We are seeking a talented Reinforcement Learning (RL) Engineer with expertise in developing and deploying RL solutions for robotics, swarm intelligence, and drone systems. The ideal candidate should possess a strong foundation in both the theoretical aspects of RL and the practical implementation of algorithms in real-world environments. You will design novel RL architectures, integrate advanced methodologies, and build scalable systems capable of managing complex distributed control problems.

Key Responsibilities:

• RL Algorithm Development & Integration: Design, implement, and optimize RL algorithms for robotic platforms, UAV swarms, and autonomous agents.
• Multi-Agent Reinforcement Learning (MARL): Build and evaluate MARL frameworks for coordination, deconfliction, and cooperative decision-making in multi-drone systems.
• Engineering & Deployment: Implement efficient training pipelines for large-scale RL simulations and optimize performance in simulation-to-real transfer for robotics and aerial vehicles.
• Research & Innovation: Stay updated with state-of-the-art RL methodologies and investigate hybrid learning paradigms (e.g., neurosymbolic methods, model-based/model-free hybrids).

Core Competencies:

• Expertise in Reinforcement Learning, including policy-gradient methods, Q-learning, and hierarchical RL.
• Hands-on experience with MARL, federated learning, and memory-augmented policies.
• Knowledge of sim2real techniques, domain randomization, and transfer learning for robotics.
• Proficiency with RL frameworks (Ray RLlib, Stable Baselines3) and simulation environments (PyBullet, Isaac Gym).
• Strong programming skills in Python and C++ for RL research and robotics middleware integration.
• Familiarity with Docker, distributed training systems, and GPU clusters.

Qualifications:

• Master's or PhD in Computer Science, Robotics, AI/ML, or a related field.
• Proven track record of implementing RL algorithms for robotics or UAV applications.
• Expertise in multi-agent systems, swarm robotics, and real-world control.
• Excellent problem-solving ability and a research-driven mindset.

Preferred (Nice-to-Have):

• Experience with safety-aware or constrained RL for critical systems.
• Background in distributed optimization or networked systems.
• Contributions to open-source RL or robotics frameworks.
• Publications in AI or robotics conferences.

TII aims to help society overcome its biggest hurdles through rigorous scientific discovery and inquiry. Our approach fosters groundbreaking advancements in AI, autonomous robotics, digital security, and more.